From brief to backlog.
Grounded in real code.
Most AI story generators write tickets in a vacuum. ArcLume reads your codebase first — then generates stories with exact file paths, line numbers, and confidence scores. Code-aware ticket generation that engineers actually trust.
Generic AI writes generic tickets.
ChatGPT, Notion AI, and other generic story generators produce plausible-sounding tickets that have no connection to your codebase. Engineers spend more time deciphering vague stories than they save.
Generic AI output
Story: Add webhook notifications
"As a user, I want to receive webhook notifications when my order ships so that I can update my systems."
Acceptance criteria:
- Webhook endpoint is configurable
- Notifications are sent in real-time
- Retry logic handles failures
No file paths. No line numbers. No awareness of existing code.
ArcLume output
Story: Emit order.shipped event from fulfillment handler
file: fulfillment-service/src/handlers/shipment.ts
lines: 47-89 (OrderShipment.complete method)
confidence: confirmed
Implementation notes:
- Extend existing BullMQ job in shipment.ts:L52
- Reuse WebhookDispatcher from shared-lib/src/webhooks.ts
- 3 downstream consumers detected (see related stories)
Exact files. Line numbers. Dependency chain mapped.
How code-aware story generation works
You describe what you want to build. ArcLume figures out where it lives in your code and generates stories that reflect your actual architecture.
Describe the feature
Upload a meeting transcript, paste a product brief, or type a one-liner. ArcLume accepts any format — it extracts the intent and requirements from natural language.
ArcLume queries the structural model
Using the feature description, ArcLume searches the structural model for relevant symbols, call chains, service boundaries, and interface points. It maps every piece of code that the feature will touch.
Stories are generated with structural context
Each story includes the specific files and line ranges to modify, the functions and classes involved, cross-service dependencies, and a confidence score indicating how certain ArcLume is about each scope element.
Refine, approve, and ship
Review the generated stories, adjust scope, add acceptance criteria, and push directly to your project tracker. Engineers pick up stories that already tell them exactly where to start coding.
Why engineers trust ArcLume stories
The difference between a story that gets refined three times and one that gets picked up immediately is structural grounding.
Precise scope
Every story pinpoints the exact files, line ranges, and functions to modify. No ambiguity about where the work lives in the codebase.
Dependency awareness
Stories surface cross-service impacts before they become mid-sprint surprises. If a change affects three repos, you get three linked stories — not one vague ticket.
Confidence scoring
Each scope element is tagged as confirmed, likely, or uncertain. Engineers know exactly what's solid and what needs verification before coding starts.
Stop writing tickets in a vacuum.
Connect your repos and generate stories that reference real files, real functions, and real dependencies. Brief to backlog in minutes.
Start generating stories